Saved datasets
Last updated
Download format
Usage rights
License from data provider
Please review the applicable license to make sure your contemplated use is permitted.
Topic
Provider
Free
Cost to access
Described as free to access or have a license that allows redistribution.
4 datasets found
  1. PAN Wikipedia Vandalism Corpus 2011 (PAN-WVC-11)

    • zenodo.org
    zip
    Updated Jun 11, 2022
    + more versions
  2. W

    Webis-WVC-07

    • webis.de
    3341473
    Updated 2007
  3. PAN Wikipedia Vandalism Corpus 2010 (PAN-WVC-10)

    • zenodo.org
    zip
    Updated Jan 24, 2020
  4. Webis Wikipedia Vandalism Corpus (Webis-WVC-07)

    • zenodo.org
    zip
    Updated Jan 24, 2020
  5. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

Share
FacebookFacebook
TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
Martin Potthast; Martin Potthast; Benno Stein; Benno Stein; Teresa Holfeld; Teresa Holfeld (2022). PAN Wikipedia Vandalism Corpus 2011 (PAN-WVC-11) [Dataset]. http://doi.org/10.5281/zenodo.3342157
Organization logo

PAN Wikipedia Vandalism Corpus 2011 (PAN-WVC-11)

Explore at:
zipAvailable download formats
Dataset updated
Jun 11, 2022
Dataset provided by
Zenodohttp://zenodo.org/
Authors
Martin Potthast; Martin Potthast; Benno Stein; Benno Stein; Teresa Holfeld; Teresa Holfeld
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Description

The PAN Wikipedia Vandalism Corpus 2011 (PAN-WVC-11) is a corpus for the evaluation of automatic vandalism detectors for Wikipedia. For research purposes the corpus can be used free of charge.

This corpus supplements the PAN-WVC-10, which features only English edits. Both corpora should be used to get more representative results.

The corpus compiles 29949 edits on 24351 Wikipedia articles, among which 2813 vandalism edits have been identified. The corpus features 9985 English edits, 9990 German edits, and 9974 Spanish edits. To annotate the corpus we have used Amazon's Mechanical Turk; each edit was presented to a number of annotators who were asked to decide whether it is vandalism or regular, and the agreement of the annotators was analyzed in order to label an edit.

Search
Clear search
Close search
Google apps
Main menu